The variational quantum eigensolver (or VQE), first developed by Peruzzo et al.(2014), has
received significant attention from the research community in recent years. It uses the …

A universal fault-tolerant quantum computer that can efficiently solve problems such as
integer factorization and unstructured database search requires millions of qubits with low …

For quantum computers to successfully solve real-world problems, it is necessary to tackle
the challenge of noise: the errors that occur in elementary physical components due to …

One of the most promising suggested applications of quantum computing is solving
classically intractable chemistry problems. This may help to answer unresolved questions …

Quantum computers can exploit a Hilbert space whose dimension increases exponentially
with the number of qubits. In experiment, quantum supremacy has recently been achieved …

The simulation of fermionic systems is among the most anticipated applications of quantum
computing. We performed several quantum simulations of chemistry with up to one dozen …

Contemporary quantum computers have relatively high levels of noise, making it difficult to
use them to perform useful calculations, even with a large number of qubits. Quantum error …

Computational models are an essential tool for the design, characterization, and discovery
of novel materials. Computationally hard tasks in materials science stretch the limits of …

The variational quantum eigensolver (VQE) is a method that uses a hybrid quantum-
classical computational approach to find eigenvalues of a Hamiltonian. VQE has been …

An important measure of the development of quantum computing platforms has been the
simulation of increasingly complex physical systems. Before fault-tolerant quantum …